TY - GEN
T1 - Classification of phyto-pathogens using infrared spectroscopy and advanced computerized methods
AU - Salman, Ahmad
AU - Shufan, Elad
AU - Tsror, Leah
AU - Moreh, Raymond
AU - Huleihel, Mahmoud
AU - Mordechai, Shaul
PY - 2013/12/1
Y1 - 2013/12/1
N2 - Fungi are serious pathogens for many plants and crops, potentially causing severe economic loss. Early detection and identification of these pathogens is crucial for their timely control. Currently existing methods available for identification of fungi are time consuming, expensive and not always very specific. We used Fourier Transform InfraRed spectroscopy (FTIR) attenuated total reflectance (ATR), combined with Principal Component Analysis (PCA), and Linear Discriminant Analysis (LDA), for differentiating fungal phyto-pathogens at the isolate level. Four different fungi genera were investigated; Colletotrichum, Verticillium, Fusarium and Rhizoctoniai. Our main goal was to differentiate these fungi samples at the level of isolates, based on their infrared (IR) fingerprint absorption spectra. Based on our computerized and objective analyses, our results are in high compliance with existing biological classification methods. FTIR, combined with advanced computerized methods, provides an inexpensive and reagentfree technique that delivers accurate results on fungi classification within few minutes. FTIR may also turn out to be an important in situ and in vivo alternative diagnostic tool in agricultural. At the generic level, the identification success rate was 97.5% using five principal components (PCs), while at the isolates level the identification success rates were 97.1%, 90%, and 89%, respectively, for Verticillium dahliae, Colletotrichum coccodes, and Fusarium oxysporum.
AB - Fungi are serious pathogens for many plants and crops, potentially causing severe economic loss. Early detection and identification of these pathogens is crucial for their timely control. Currently existing methods available for identification of fungi are time consuming, expensive and not always very specific. We used Fourier Transform InfraRed spectroscopy (FTIR) attenuated total reflectance (ATR), combined with Principal Component Analysis (PCA), and Linear Discriminant Analysis (LDA), for differentiating fungal phyto-pathogens at the isolate level. Four different fungi genera were investigated; Colletotrichum, Verticillium, Fusarium and Rhizoctoniai. Our main goal was to differentiate these fungi samples at the level of isolates, based on their infrared (IR) fingerprint absorption spectra. Based on our computerized and objective analyses, our results are in high compliance with existing biological classification methods. FTIR, combined with advanced computerized methods, provides an inexpensive and reagentfree technique that delivers accurate results on fungi classification within few minutes. FTIR may also turn out to be an important in situ and in vivo alternative diagnostic tool in agricultural. At the generic level, the identification success rate was 97.5% using five principal components (PCs), while at the isolates level the identification success rates were 97.1%, 90%, and 89%, respectively, for Verticillium dahliae, Colletotrichum coccodes, and Fusarium oxysporum.
KW - Colletotrichum coccodes
KW - FTIR-ATR
KW - Fungal detection
KW - Fusarium oxysporum
KW - LDA
KW - PCA
KW - Rhizoctonia solani
KW - Verticillium dahliae
UR - http://www.scopus.com/inward/record.url?scp=84893142342&partnerID=8YFLogxK
M3 - Conference contribution
SN - 9781936338924
T3 - IMETI 2013 - 6th International Multi-Conference on Engineering and Technological Innovation, Proceedings
SP - 14
EP - 19
BT - IMETI 2013 - 6th International Multi-Conference on Engineering and Technological Innovation, Proceedings
T2 - 6th International Multi-Conference on Engineering and Technological Innovation, IMETI 2013
Y2 - 9 July 2013 through 12 July 2013
ER -